deep-q-learning

Implementations from the free course Deep Reinforcement Learning with Tensorflow and PyTorch

Stock Trading Bot using Deep Q-Learning

A curated list of Monte Carlo tree search papers with implementations.

A PyTorch library for building deep reinforcement learning agents.

CURL: Contrastive Unsupervised Representation Learning for Sample-Efficient Reinforcement Learning

Deep Q-learning for playing flappy bird game

Deep Q-learning for playing tetris game

RAD: Reinforcement Learning with Augmented Data

Trained A Convolutional Neural Network To Play 2048 using Deep-Reinforcement Learning

A Deep Reinforcement Learning Framework for Stock Market Trading

Project on design and implement neural network that maximises driving speed of self-driving car through reinforcement learning.

Solutions of assignments of Deep Reinforcement Learning course presented by the University of California, Berkeley (CS285) in Pytorch framework

SUNRISE: A Simple Unified Framework for Ensemble Learning in Deep Reinforcement Learning

Train a DQN Agent to play CarRacing 2d using TensorFlow and Keras.

DQN, DDDQN, A3C, PPO, Curiosity applied to the game DOOM

PyTorch implementation of the Munchausen Reinforcement Learning Algorithms M-DQN and M-IQN

Reinforcement learning algorithm implementations and ML experimentation workspace

Reinforcement Learning Agent for Binance Futures — realistic backtesting, CNN + D3QN + PER, and reproducible training pipeline.

A collection of several Deep Reinforcement Learning techniques (Deep Q Learning, Policy Gradients, ...), gets updated over time.

Using deep reinforcement learning to tackle the game 2048.